Shiqi Wang
Columbia University, United States
Summary
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SeniorShiqi Wang is an AI research scientist and core contributor to Amazon CodeWhisperer and the Alpha-Beta-CROWN project, specializing in building and deploying large language models for code with a focus on reasoning, coding performance, and trustworthiness. With a PhD in Computer Science from Columbia and eight years of experience across industry research roles at AWS, Meta, and internships at Microsoft, IBM, and Baidu, she bridges cutting-edge research and production-grade ML systems. She led major pre- and post-training efforts, instruction tuning, and robust fine-tuning pipelines for Amazon Q inline (CodeWhisperer) and has authored multiple top-tier conference papers tied to product impact. Now at Meta’s TBD Lab, she continues to advance LLM code reasoning and RL-based approaches, bringing a rare combination of deep verification-oriented research (e.g., ABCROWN) and hands-on deployment experience. Notably, she has driven launches and tutorials that translate research insights directly into developer-facing tooling.
9 years of coding experience
Github Skills (12)
robustness10
formal-verification9
security8
gpu7
kubernetes7
benchmarking7
adversarial-machine-learning6
neural-network5
benchmark4
branch-and-bound3
machine-learning3
gcp1
Programming languages (3)
Github contributions (5)
tcwangshiqi-columbia/Neurify
Oct 2018 - Jul 2020
The released code of Neurify in NIPS 2018
Contributions:37 commits, 2 PRs, 33 pushes in 1 year 9 months
releasednips-2018kubernetesnips
tcwangshiqi-columbia/symbolic_interval
Feb 2019 - Jan 2020
The library for symbolic interval
Contributions:64 commits, 17 pushes in 11 months
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